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Atlantic Review of Economics 

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Colegio de Economistas da Coruña
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Volumen 1 Número 11: Income and income Redistribution in 1996 Hungary is in line with OECD members.

Erzsébet Kovács
Budapest University of Economics Sciences and Public Administration

Zoltán Kollár
Budapest University of Economics Sciences and Public Administration

Reference: Received 04th June 2002; Published 04th October 2002. ISSN 1579-1475

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This paper examines the homogeneity of the OECD member states in 1996. Besides the free-market industrialized countries the database contains the Czech Republic, Hungary and Poland, as three new members of the Organization for Economic Cooperation and Development (OECD). International comparison is conducted on the basis of general income indicators, among them the GDP per capita using current exchange rates and current purchasing power parities (PPP). Investigating the effect of the GDP level and of taxation on disposable income and on final consumption in the OECD countries, present paper deals with the statistical similarity of members. Different classifications of countries are presented using multivariate statistical procedures (cluster analysis and multidimensional scaling).

Organization for Economic Cooperation and Development set up to assist member states to promote sustained economic growth with financial stability. Mexico joined to this international organization in 1993, and the Czech Republic became member in 1995. Hungary and Poland joined in 1996. These three transition countries are compared to the other 25 OECD members . According to the approach applied, free market and high income level are the basic requirements expected to fulfill by the new member states. In order to measure the similarity in the OECD, we first of all need to introduce the newcomers.
The Czech Republic, Hungary and Poland, the former planned economies have started the economic transition in the late 80´s, early 90´s, and have already gone through stabilization, price liberalization, privatization and restructuring. Economic reform in other countries is a more recent process. In spite of the common name (transition countries) there are extremely big differences in Central- Eastern Europe taking into account gross domestic product (GDP) level as well as change in GDP per capita, inflation, foreign direct investment, etc. The issue is not whether to go to a market economy but how to get there.
On the other hand there are similarities in the transition process of Eastern and Central Europe:

1) Stabilization has been associated with a sharp initial decrease in measured output. There are serious problems of (mis)measurement of GDP and the performance of the new private sector. Only Poland could reach 112 per cent of its (very low) 1989´s GDP in 1997. The decline in output has characterized Hungary in the past decade. The Hungarian GDP was only 90 per cent of the 1989´s level in 1997.
2) The private sector has done well and (in some countries) replaced the state sector. The unemployment rates were reduced by small businesses and increasing rates of self-employment. The private export has increased, but the share of total export in GDP shows different pictures. The proportion of the export became higher in Czech Republic (38 and 48 per cent), decreased in Hungary (34 and 29 per cent) and it is at the same level (20 per cent) as it was in Poland in 1989. There has been some shift of export markets because of trade liberalization. International competition was introduced into the domestic markets. In some countries convertibility (at least in the field of trade transactions) was part of the monetary reform.
3) Implementing privatization has proved to be harder and slower than expected. Most governments face current budget deficit problems resulting partly from the declining revenues from the profit tax on state enterprises. Restructuring has been less than is needed. Decentralized and profit-maximizing ownership will be not necessarily sufficient to restructuring the economy.

4) Stabilization and price liberalization have led to a large price adjustment. In addition to this effect the initial devaluation has contributed to the high inflation. Subsidies and allowances provided at the cost of the state have been cut or eliminated. Income distribution has changed, income inequality has continued to grow.
5) The extensive shadow economy is present in all of the transition countries. Unregistered economic activity is present in a number of sectors. Jobs are provided, goods and services are produced in the shadow (or gray) economy, estimated to contribute to GDP in a range of 15 to 50 per cent. A significant part of the income of these countries is generated outside the registered economy, and taxation is avoided due to poor tax administration. Official figures on income distribution and actual dispersion are far from the ultimate levels of disposable real income.
Summarizing these characteristics it seems feasible to claim that mixed trends can be observed. Due to the decrease in the officially measured output and privatization the social security budget is decreasing. People are encouraged to take care for themselves, to buy life and health insurance, to become members of private pension funds, etc., as it is common in the market economies.

Analysis and Methods
Prior Research
During the last four years, the current authors undertook studies to determine the most important differences in taxation to compare the government expenditure structure of upper and upper-middle income countries. In addition the differences between demographic indicators and employment characteristics were tested. The following conclusion was drawn: Hungary is similar to Latin American countries and to the "less-developed" OECD-members focusing on those indicators which are income dependent. At the same time there are special indicators (for example self-employment, female participation rates, taxation) where position of Hungary is relatively similar to the highly developed EU-countries. The three transition countries, the Czech Republic, Poland and Hungary are less similar to each other than it is assumed at the first glance.

Data and Methods
International comparison is conducted on the basis of general income indicators, among them the GDP per capita using current exchange rates and current purchasing power parities (PPP). Besides Hungary our data base contains the Czech Republic and Poland, all of them are new members of the OECD. Comparison of the other transition countries would be interesting, but data from the years of transition are extremely variable and in some cases missing. To meet the overall reliability, consistency and comparability of data the OECD Observer is used for statistical comparison. Cross-country analysis is presented using data for 1996. Classification of countries will be described using multivariate statistical methods. Correlation coefficients are calculated to check the sign and the strength of linear relations to avoid the problem of multicollinearity. Hierarchical and non-hierarchical cluster analysis and non-metric multidimensional scaling are conducted to compare the OECD member states.

Analysis of Results
Summary Statistics for the OECD member states
Table 1 presents means and standard deviations of variables selected for the further analysis.
Differences among the OECD members are characterized by the coefficient of variation. Most of the values are reasonable, except for 0.53 coefficient calculated for the GDP per capita.

Statistically significant Pearson correlation coefficients are presented in Table 2. The per capita GDP level is not correlated significantly with other variables. Health expenditure is the only variable positively connected to the increase of the GDP. There are obvious results in Table 2: increasing tax as percent of GDP will increase the government final consumption and at the same time will reduce the disposable income proportion of a single worker.

Based on the missing (low) correlation values nonlinear tendency is stated. Proportion of final consumption can be high or can be low at different income levels. Income redistribution indicators and the per capita GDP values are spreaded in Figure 1.

Comparison of income levels
The transition process in our region is combined with the clear vision of developed market economy integrated into the European Union. Most of the economic experts agree: sooner or later the transition economies will be on the rise. But the increasing rate of growth does not mean similar income level in the short run. Poland has enjoyed a remarkable rate of growth, but the leader position disappears taking into account the actual GDP per capita level. There are extremely great differences in this respect: Poland has got 12 per cent of the OECD average in 1996, while Hungary and the Czech Republic have reached 21 per cent of the OECD average. Prices of goods and services are relatively high in the OECD. The GDP per capita at purchasing power parities (PPP´s) is only 87 per cent of the actual GDP. The PPP based calculation moves the GDP per capita in the opposite direction for the three transition countries. The Czech Republic produced 69 per cent, Hungary reached 49 per cent, and Poland was at 41 per cent of the OECD average GDP at PPP´s in 1996. Figure 2 shows both of the GDP measures.

Four countries (Denmark, Japan, Norway and Switzerland) are in the top income group (above 30000 US dollar per capita) and sharp reduction s visible in their purchasing powers. The other 15 highly developed countries are in the second group. Their GDP per capita levels are higher than 18000 US dollar, but the purchasing power parity reduces this amount. Spain follows this group with 15000 US dollar at current price and PPP as well. The third group contains eight countries with less than 12000 US dollar: Czech Republic, Greece, Hungary, Korea, Mexico, Poland, Portugal, and Turkey. The purchasing powers in this group are significantly higher the current GDP per capita levels.
The greatest achievement of economic transition is that the market economy already exists, but the Central-Eastern European income level is still not compatible to the industrialized European countries.

Results on disposable income, final consumption and tax receipts
In spite of great differences in GDP levels it is worth to compare the redistribution of the income. Five variables were selected, squared Euclidean distances were calculated to compare countries pair by pair. Seven cluster methods can be used for combining countries, but the results are strongly method dependent. The graph of the hierarchical classification conducted by Ward Method is shown on Figure 3. Figure 4 is prepared by average linkage, between group distance cluster method. In spite of the mathematical differences there is some stability in the classification.
Spain, Switzerland, Portugal and Poland create the first small group in both dendrograms. Hungary joins to Austria, France and the Czech Republic, and some other parts of these figures show combination of countries with completely different income level. Countries with upper and upper-middle income level are not found in the same cluster, and are similar to less developed countries measuring income allocation through disposable income, final consumption and tax receipts.
Investigating these two dendrograms 3-5 groups can be identified. Figure 3 and Figure 4 present 3 well-separated clusters at a higher rescaled distance, and 4-6 smaller groups at lower distance level. Iceland and Turkey have to be mentioned as outliers on both figures.


To check the sensitivity of the above hierarchical classification nonhierarchical clustering can be used. Dividing countries into groups, it is obvious that high total tax receipts supports high level of government final consumption, and results lower private final consumption proportion. At the same time the disposable income depends on the income redistribution scheme, and this spending is determined by political decision. Table 3 presents the result of clustering countries into three groups.

Cluster I is the biggest group with 11 members. The highest private final consumption rate and the lowest tax proportion belong to this group. It can be a great surprise to see Turkey and Mexico together with the UK, Ireland, Greece, Italy, Spain and other four non-European countries (US, Canada, New-Zealand and Australia). This group can be separated into subgroups taking into account Figure 3 and Figure 4.
Cluster II contains the transition countries (Czech Republic, Hungary and Poland) together with Austria, Iceland, Japan, Korea, Portugal and Switzerland. These countries are characterized by high redistribution, and support families strongly. This group is an interesting mixture of four rich countries and five countries from the poorest seven. Korea and New-Zealand are extremely far from the cluster center and there are big within group distances (see Figure 5).
Countries from the third cluster are called welfare societies: Belgium, Denmark, Finland, France, Germany, the Netherlands, Norway and Sweden. These 8 countries collect the highest percentage of the GDP as taxes resulting the smallest disposable income percentages.

Increasing the number of clusters new and more reliable classification can be prepared. All of the five variables are significant in the k-means clustering procedure when countries are divided into seven clusters.
The final cluster centers are presented in Table 4.


According to this classification three countries are alone in Cluster 3, 4 and 5. Turkey is the only member of Cluster 3 with the lowest rate of tax receipts and we can find here the minimum percentage of the family disposable income. The private final consumption rate is very high in Greece, so this country is alone in Cluster 4. Iceland is unique (in Cluster five) because of the extremely high family support. Disposable income of an Iceland´s family (with two children) is 114,5 per cent of the worker´s gross pay.
Hungary with Czech Republic, Austria, France, Ireland and Norway are members of Cluster 1. Running different procedures the first four countries remained together. The minimum of the private final consumption percentage belongs to this cluster, but the government final consumption expenditure and the tax receipts reach quite high proportions. Austria is very close to the cluster center.
The second group is the largest cluster combining 10 countries. Not only the highly industrialized countries (among them Spain, UK, US) are members of Cluster 2, Poland is classified into this group as well. They do not have any extreme character, their five indicators show moderate level. This group is less heterogeneous than the first one.
Cluster 6 contains two subgroups, which are present on Figure 3 and 4 as well. Finland, Sweden and Denmark are classified together with Belgium, Germany and the Netherlands in Cluster 6. The maximum tax receipts combined with the lowest disposable income as percentage of gross pay for a single worker are describing these welfare countries. Finland is very close to the cluster center.
Cluster 7 has three members: Japan, Korea and Mexico. Their common feature is the small total tax receipts to the GDP, and the governments spend the minimum percentage of GDP for final consumption expenditures in these countries.
Figure 6 is a boxplot presenting the distribution of within group distances for seven clusters. Clusters covering only one members, have got zero distance values.

Comparing this classification to the results based on income levels obvious differences can be mentioned. The per capita GDPs of eight countries were below 12000 US dollar (Figure 2), but members of this group are divided into 6 clusters according to the final consumption and disposable income proportions.
Japan from the top income group is now together with Korea and Mexico, and the other 14 developed countries are classified into smaller clusters. Czech Republic and Hungary "insist on" being together with Austria and France. Poland is together with its previous cluster members, like Portugal and Spain.
These changes can be explained by bilateral comparisons and some other factors, like historical traditions and political decision on income centralization. As far as we can state the income redistribution does not depend on the income level of the OECD countries. Table 5 is a crosstable of cluster structure according to GDP classification and allocation of the national products.

Our hypothesis about the independence of these two classifications cannot be rejected. The Pearson CHI-square value is smaller than the critical value. (CHI- square is 7.4, with 4 degrees of freedom and the critical value of the test is 9.49 at 5 per cent significance level.)
At a lower income level the governments have limited freedom to decide on expenditure structure and the disposable income proportion. Supposing reasonable increase of the GDP level in the transition countries, the governments will face options how to balance financial position of people. One solution is open for everyone: take care themselves buying life and non-life insurance policies or to enter private pension funds.

This paper has estimated the relative effect of GDP level to disposable income and final consumption in OECD countries. The analysis was performed using data of 1996. Country-specific models were found for the income redistribution, but the per capita GDP level and the allocation of the nation product proved to be independent. There is no unique model for transition countries in this field. The statistical proximity does not prove similar economic policy. The analysis raises questions about the interaction between GDP level and government´s decision, as well as on employee´s self care. Bilateral international comparison seems to be vital, and tradition of social security system, and health care have to be investigated. Transition countries have to look for short run and long run adjustment mechanisms to avoid temporary or permanent decrease in final consumption and thin social security net.


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About the Authors

Dr. Erzsébet Kovács
Budapest University od Economic Sciences and Public Administration
Fövám ter 8. Budapest, h-1093. Hungary

Phone/fax: +36-1-2176725

Dr. Zoltán Kollár
Budapest University od Economic Sciences and Public Administration
Fövám ter 8. Budapest, h-1093. Hungary

Phone/fax: +36-1-2176725



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V. Salcines. (Universidade da Coruña)
Andrés Blancas. Instituto de Investigaciones Económicas (UNAM)
Editor Asociado para America Latina:
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